The present invention relates to blind equalization techniques to compensate for channel transmission distortion in digital communication systems. In particular, the present invention relates to an equalization technique for use with trellis-encoded data such as that adopted by the U.S. for broadcast transmission of high definition television (HDTV) signals.
Digital transmission of information typically involves the modulation of pulses on the amplitude and/or phase of an RF carrier. A propagation medium such as terrestrial broadcast introduces signal distortion caused by noise (static), strength variations (fading), phase shift variations, multiple path delays, and the like.
In addition, multiple different paths between the transmitter and receiver through the propagation medium cause multiple path delays. The different paths have different delays that cause replicas of the same signal to arrive at different times at the receiver (like an echo). Multi-path distortion results in inter-symbol interference (ISI) in which weighted contributions of other symbols are added to the current symbol.
In addition to distortion and noise from the propagation medium, front-end portions of the receiver and transmitter also introduce distortion and noise. The presence of distortion, noise, fading and multi-path introduced by the overall communication channel (transmitter, receiver and propagation medium), can cause digital systems to degrade or fail completely when the bit error rate exceeds some threshold and overcomes the error tolerance of the system.
Digital systems transmit data as symbols having discrete levels of amplitude and/or phase. The digital receiver uses a slicer to make hard decisions as to the value of the received symbol. A slicer is a decision device responsive to the received signals at its input, which outputs the nearest symbol value from the constellation of allowed discrete levels. A slicer is also known as a nearest element decision device. To the extent that a symbol is received at a level that differs from one of the allowed discrete levels, a measure of communication channel error can be detected.
At the receiver, it is known to use an equalizer responsive to the detected error to mitigate the signal corruption introduced by the communications channel. It is not uncommon for the equalizer portion of a receiver integrated circuit to consume half of the integrated circuit area.
An equalizer is a filter that has the inverse characteristics of the communication channel. If the transmission characteristics of the communication channel are known or measured, then the equalization filter parameters can be determined. After adjustment of the equalization filter parameters, the received signal is passed through the equalizer, which compensates for the non-ideal communication channel by introducing compensating xe2x80x9cdistortionsxe2x80x9d into the received signal which tend to cancel the distortions introduced by the communication channel.
However, in most situations such as in HDTV broadcasting, each receiver is in a unique location with respect to the transmitter. Accordingly, the characteristics of the communication channel are not known in advance, and may even change with time. In those situations where the communication channel is not characterized in advance, or changes with time, an adaptive equalizer is used. An adaptive equalizer has variable parameters that are calculated at the receiver. The problem to be solved in an adaptive equalizer is how to adjust the equalizer filter parameters in order to restore signal quality to a performance level that is acceptable by subsequent error correction decoding.
In some adaptive equalization systems, the parameters of the equalization filter are adjusted using a predetermined reference signal (a training sequence), which is periodically re-sent from the transmitter to the receiver. The received training sequence is compared with the known training sequence to derive the parameters of the equalization filter. After several iterations of parameter settings derived from adaptation over successive training sequences, the equalization filter converges to a setting that tends to compensate for the distortion characteristics of the communications channel.
The U.S. standard for broadcast transmission of high definition television (HDTV) signals embeds a recurring training sequence every 24 milliseconds. Unfortunately, for terrestrial broadcast the propagation medium often undergoes time-varying inter-symbol interference characteristics, for example due to such subtle changes as foliage waiving in the wind, which prevent the successful convergence of an equalizer that relies solely on the training sequence for convergence. Therefore, a blind equalization technique is highly desirable.
In blind equalization systems, the equalizer filter parameters are derived from the received signal itself without using a training sequence. In the prior art, it is known to adjust the equalizer parameters blindly using the Least Mean Squares (LMS) algorithm, in which the training symbols are replaced with hard decisions, or best estimates of the original input symbols. Blind equalization systems using LMS in this manner are referred to as decision directed LMS (DD-LMS).
However, the DD-LMS algorithm requires a good initial estimate of the equalizer parameters. For most realistic communication channel conditions, the lack of an initial signal estimate of the equalizer parameters results in high decision error rates, which cause the successively calculated equalizer filter parameters to continue to fluctuate, (diverge or go to +/xe2x88x92infinity), rather than converge to a desired solution.
It is also known to use another algorithm, called the Constant Modulus Algorithm (CMA), in combination with the DD-LMS algorithm from a cold start. The CMA algorithm is used first to calculate the equalizer filter parameters, which is regarded as an initial estimate. Thereafter, the equalizer filter parameters (as calculated by the CMA algorithm) are used in an acquisition mode to find the initial equalizer filter parameters to start the DD-LMS algorithm.
The Constant Modulus Algorithm (CMA) was originally proposed by Godard for QAM signals. See D. N. Godard, xe2x80x9cSelf-recovering equalization and carrier tracking in two-dimensional data communication systems,xe2x80x9d IEEE Transactions on Communications, vol 28, no. 11, pp. 1867-1875, November 1980. A similar technique was independently developed by Treichler and Agee for constant envelope FM signals. See J. R. Treicher, B. G. Agee, xe2x80x9cA new approach to multipath correction of constant modulus signals,xe2x80x9d IEEE Transactions on Acoustics, Speech, and Signal Processing, vol. ASSP-31, no. 2, pp. 459-472, April, 1983. Godard""s original intention was to develop an algorithm that was insensitive to carrier synchronization in order to decouple equalization and carrier tracking, so that carrier tracking could be done in a decision directed (DD) mode. The satisfaction of the latter goal is the single-most attractive feature of CMA, which accounts for its widespread deployment today. See J. R. Treichler, M. G. Larimore, J. C. Harp, xe2x80x9cPractical Blind Demodulators for High-Order QAM signals,xe2x80x9d Proceedings of the IEEE, Vol. 86, No. 10, pp. 1907-1926, October 1998.
The CMA algorithm (as well as the DD-LMS algorithm) is usually implemented with a gradient descent strategy in which the equalizer parameters are adapted by replacing the present equalizer parameter settings with their current values plus an error (or correction) term. See C. R. Johnson, Jr., P. Schniter, T. J. Endres, J. D. Behm, D. R. Brown, R. A. Casas, xe2x80x9cBlind equalization using the constant modulus criterion: a review,xe2x80x9d Proceedings of the IEEE, vol. 86, no. 10, pp. 1927-1950, October, 1998. The CMA error term itself is a cubic function of the equalizer output.
The CMA algorithm may be modified for use with an equalizer for a high definition television (HDTV) receiver. In the U.S. HDTV standard, a carrier signal is amplitude modulated to one of 8 levels in a scheme known as 8-VSB (Vestigial Sideband) modulation. Each of the transmitted symbols is represented by a 3-bit code. The 8-VSB symbols are trellis encoded and interleaved in time. CMA is adapted for an 8-VSB HDTV signal by applying the Constant Modulus (CM) criterion to only the real part of the equalizer output. The imaginary component of the equalizer output is not calculated. The modified adaptive algorithm is referred to as Single Axis CMA (SA-CMA).
From a cold start, the receiver enters an acquisition mode. In the acquisition mode, the CMA algorithm is used first to adjust the equalizer parameters. Then, after a fixed period of time such as a fixed number of training sequences (or alternatively based on a measure of signal quality that is derived from the equalizer output), the receiver switches to the DD-LMS algorithm in a tracking mode. The acquisition mode typically requires up to 400,000 symbols. At a 10 MHz clock rate, the symbol rate is 100 nanoseconds and the time available for acquisition using the CMA algorithm is about 40 milliseconds.
The CMA algorithm is applicable to signals that have symbol values of constant magnitude, such as Quadrature Phase Shift Keying (QPSK). CMA also works for higher-order constellations containing symbol values of multiple magnitudes. However, the CMA algorithm suffers a high residual jitter in its steady state error. The resulting stochastic jitter, or misadjustment, is quantified by Fijalkow. See I. Fijalkow, C. E. Manlove, C. R. Johnson, Jr., xe2x80x9cAdaptive fractionally-spaced blind CMA equalization: excess MSE,xe2x80x9d IEEE Transactions on Signal Processing, vol. 46, pp. 227-231, Janurary 1998. Jitter is the tendency of a control system to fluctuate (i.e., xe2x80x9cjitterxe2x80x9d) above and below a steady state value.
The present invention is embodied in a method and apparatus for reducing stochastic jitter in a blind equalizer using the CMA algorithm, thereby improving the performance of the CMA algorithm. Improved performance is obtained by using a partial trellis decoder to predict 1 bit or 2 bits of the next corresponding 3-bit transmitted symbol. The predicted bits from the partial trellis decoder are used to reduce the effective number of symbols in the source alphabet. Specifically, an 8-VSB signal has 8 levels and a source alphabet of 8 symbols. If 1 bit of the subsequent 3-bit symbol is predicted, the number of permissible signal levels is reduced to 4 levels, which reduces the effective number of symbols in the source alphabet to 4 equally probable symbols. If 2 bits of the subsequent 3-bit symbol is predicted, the number of permissible signal levels is reduced to 2 levels, which reduces the effective number of symbols in the source alphabet to 2 equally probable symbols. The invention is applicable to coding schemes in which at least one bit of a received symbol can be determined from one or more prior symbols. If so, then at least one bit of the present symbol can be predicted in advance and used to reduce the effective number of symbols in the source alphabet seen by the CMA algorithm. The invention is thus applicable to many codes, including other trellis codes as well as to non-trellis codes.
Reducing the effective number of symbols in the source alphabet for soft decision CMA (blind) equalization is analogous to reducing the number of slicer levels in a hard decision, nearest element decision device. Reducing the number of slicer levels increases the (Euclidean) distance between decision levels in a slicer. An increased Euclidean distance between decision levels reduces the chance that the channel distortion will cause a symbol decision error, which improves convergence performance. In a hard decision, nearest element decision device, the effective slicer decision levels are changed in accordance with the predicted bit(s). In the present invention, the received input signal to blind equalization error calculation is offset, i.e., shifted up or down by a computed xcex94 in accordance with the predicted bit(s). In addition, when applied to CMA for blind equalization, a different constant, the Godard radius xcex3, for the CMA error calculation is selected in accordance with the predicted bit(s).
The equalizer method and apparatus of the present invention particularly applies to television receivers compatible with the U.S. HDTV transmission standard. In particular, the U.S. HDTV standard uses trellis encoding and data symbol interleaving. Trellis coding is well known. Data symbol interleaving is also a known technique used to mitigate the effects of burst errors (sequential errors resulting from a burst of static that can overwhelm the error correction capacity of the error coding subsystem). Data symbol interleaving (at the transmitter) and subsequent data symbol de-interleaving (at the receiver) spreads out the consecutive burst errors to different non-consecutive positions in the de-interleaved signal. In particular, in the U.S. HDTV transmission standard, data symbol interleaving is implemented on a 12-interval basis.
As a result, the ATSC standard for U.S. broadcast transmission of 8-VSB HDTV signals uses twelve parallel trellis encoders of the kind shown in FIG. 5. The 12 parallel trellis encoders are chosen sequentially in a circular manner to form a 12-interval symbol interleaver, as illustrated in FIG. 4 (ATSC Digital Television Standard Doc A/53). See Advanced Television Systems Committee (ATSC) Digital Television Standard, Document A/53, September 1995, downloadable from http:// www.atsc.org/ Standards/ A53/.
The time lag resulting from the 12-interval symbol interleaving of the parallel trellis encoders is exploited to perform partial trellis decoding between successive data symbols received 12 symbol intervals apart. Each partial trellis decoder uses one or two prior data symbols to predict one bit (Z0) or two bits (Z0 and Z1) of the subsequent data symbols. By predicting 1 bit, Z0, the 8-level VSB signal is partitioned into two sets of four elements. By predicting 2 bits, Z0 and Z1, the 8-level VSB signal is partitioned into four sets of two elements.
In such manner, either a 2-level or 4-level signal (a set partitioned signal) is created from the 8-VSB signal. The bit estimates obtained from partial trellis decoding are thus used to reduce the number of hard decision levels in the slicer. With fewer slicer levels, the decision levels in the slicer are further apart, which reduces jitter and improves the convergence performance of the CMA blind equalization technique.
The predicted bit estimates are used to calculate the CMA error term used for updating the parameters of an adaptive CMA blind equalization filter. The error term (which is used in a cost function having a stochastic gradient descent) is calculated solely based on the received signal and a few known constants. The Constant Modulus criterion is applied to the set-partitioned signal so that the excess mean squared error, or stochastic jitter, is reduced. The resulting algorithm is referred to as low jitter CMA (LJ-CMA).
Initially on signal acquisition, the CMA equalizer mode is set for 8 symbol levels. After operating at 8 symbol levels for a first period of operation, the CMA equalizer mode is set for 4 symbol levels. After operating with 4 levels for a second period of operation, the CMA equalizer mode is set for 2 symbol levels. The criteria for switching the CMA equalizer from 8 levels, to 4 levels to 2 levels is based on any one of suitable convergence criteria: a fixed time interval, the signal to noise ratio, the bit error rate or number of consecutive training sequences encountered.
The latency associated with having 12 parallel trellis encoders means that there are twelve symbol intervals before the next symbol arrives for a given trellis encoder. Thus, there is sufficient time (12 symbol intervals) to estimate bits Z0 and Z1 for each of the parallel trellis encoders. U.S. patent application Ser. No. 09/099730, filed Jun. 19, 1998 to Hulyalkar et al., and assigned to the assignee of the present application describes several implementations whereby a bank of partial trellis decoders are used to estimate either bit Z0 or both bits Z0 and Z1.